Very interesting to see the range of peoples' preferences. I would almost always prefer smart over fast; I have all my LLMs to be all-thinking-all-the-time.

It’s a balance, I haven’t felt like codex provided anything that Sonnet 4.5 didn’t. Why wait longer for getting the same results.

Though that does bring up an interesting point. Anecdotally, Sonnet does a lot more grep-ing while Codex reads files straight up. Might be the difference in speed and maybe smarter models will do better. Once this model is on copilot, I can test it out.

GPT-5 was recently updated to make it more "thinking" and "warmer" or whatever and now a task (semantically compare these two short files) that used to take 5 seconds and reliably produce useful and consistent output now takes 90 seconds to "think" (while it's thinking output makes it pretty clear there is zero thinking happening) and produces a completely differently structured output every single time, making the tool not only slower and more expensive to use, but worse at a simple task that LLMs should be very good at.

There's an option to "get a quick answer" and I hoped clicking that would revert to previous performance and instead what it does is ignore that I uploaded two files and asks me to upload the files

Literally the only real good task I've found for these dumb things and they still found a way to fuck it up because they need to keep the weirdos and whales addicted. It's now almost easier to go back to comparing these files by eye, or just bite the bullet and finally write a few lines of python to actually do it right and reliably.